Looking for the crystal ball in unscheduled care: a systematic literature review of the forecasting process

Abstract

The ability to accurately forecast unscheduled care needs is of paramount importance for decision making in healthcare operations, ensuring a continuous and high-quality level of care. In this work, we provide a literature review of 156 research articles of forecasting applications with special focus on care services that are not scheduled in advance such as emergency departments. Our paper presents two key contributions. Firstly, we propose a novel framework designed to characterize the application of forecasting process across various unplanned healthcare services. Our taxonomy facilitates the detection, decomposition, and categorization of forecasting processes, enhancing the understanding of their deployment in different unscheduled care settings. Secondly, we conduct a comprehensive literature review based on a systematic search, critically analyzing the state of forecasting research in unscheduled care services and identifying key research gaps. We explore forecasting problems in depth, examining their purpose, the various methodologies used, the rigor used in generating and evaluating forecasts, and the reproducibility of results, all within the context of the proposed framework. By consolidating the current state of the art, this paper provides valuable insights to both healthcare professionals and academics regarding the effective application of forecasting in unscheduled care services. Finally, it serves as a roadmap for identifying major research gaps and outlines an agenda for future investigations.

Keywords: Classification; Forecasting; Healthcare; Regression; Time series; Unscheduled care.

Fig. 1

PRISMA diagram detailing the search process [21]

Fig. 2

Forecasting in unscheduled care services: a framework

Fig. 3

Step-by-step guide for practitioners

Fig. 4

Interaction between unscheduled care services spectrum and planning and decision levels

Fig. 5

Interaction between unscheduled care services spectrum and forecasting methods

Fig. 6

Interaction between planning and decision levels and forecasting methods

Fig. 7

Forecasting methods used in the unscheduled care literature

Fig. 8

Scatter plot illustrating datasets utilized in the literature, categorized by length and time granularity